Identification of natural fractures in wellbore images using machine learning

    公开(公告)号:US10977489B2

    公开(公告)日:2021-04-13

    申请号:US16182818

    申请日:2018-11-07

    摘要: A system, method and program product for processing borehole images to delineate between natural fractures and induced fractures. A system is disclosed that includes: an image analysis platform that inputs a noisy image from a borehole, processes the image using a set of filtering strategies, and renders a set of suggested filtered images via a user interface, the user interface including a mechanism for allowing a user to choose a selected filtered image from the set of suggested filtered images that best delineates between natural fractures and induced fractures, and wherein the image analysis platform further includes a feedback system for packaging and outputting the noisy image and selected filtered image as feedback; and a learning platform having a knowledge registration system that collects and stores training data and the feedback and in a knowledgebase, and a machine learning system that generates filtering strategies.

    Uncertainty visualization
    6.
    发明授权

    公开(公告)号:US10546394B2

    公开(公告)日:2020-01-28

    申请号:US15246648

    申请日:2016-08-25

    IPC分类号: G06T11/00

    摘要: A system, method and program product for annotating visualizations with uncertainty information. A system is provided that includes a visualization importer that imports a generated visualization; an uncertainty processor that locates a region of uncertainty in the generated visualization; and a graphics annotator that generates an annotated visualization having uncertainty artifacts that visually identify the region of uncertainty.

    CROSS-DOMAIN COLLABORATIVE DATA LOG
    9.
    发明申请

    公开(公告)号:US20180114190A1

    公开(公告)日:2018-04-26

    申请号:US15333710

    申请日:2016-10-25

    IPC分类号: G06Q10/10 G06F17/30

    摘要: A system, method and program product for a computer-based project collaboration system using a data log for cross-domain collaboration. A cognitive log stores log entries based on domain-specific project data sources. An ontology translator includes domain-specific ontologies and a mapping ontology that defines relationships among the domain-specific ontologies. A cross-domain query includes domain parameters from one domain-specific ontology and returns and displays results based on log entries with domain parameters from another domain-specific ontology using the ontology translator.